A methodology for measuring the characteristic curvature of technical-grade ethoxylated nonionic surfactants: the effects of concentration and dilution
Bibliographic record
Abstract
Abstract Characterization of the behaviour of commercially available non-ionic surfactants has received considerable attention due to their efficacy in a variety of applications. The main challenge in the application of these types of surfactants is that the hydrophilicity of the surfactant varies with concentration and dilution due to the polydispersity of the ethylene oxide groups. The hydrophilicity of a surfactant can be quantified by the characteristic curvature (Cc) parameter of the hydrophilic–lipophilic difference (HLD) framework. In this work, a model based on natural logarithmic regression was developed to calculate the Cc value of commercial surfactants as a function of surfactant concentration by a fast and simple phase scan. The slope of the Cc curve and the measured Cc at a reference concentration were used to develop the model. The Cc values determined with the model agreed with the measured values from the phase scans. Furthermore, the linear mixing rule proved to be reliable for mixtures of polydisperse ethoxylated surfactants. Finally, the impact of the water-to-oil ratio on the Cc was evaluated and the implications were discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".